Runoff - Aerial Artificial Intelligence Land Use mapping Demonstrator

Runoff - 航空人工智能土地利用测绘演示器

• 批准号: ST/V001442/1
• 负责人: Paul Scholefield
• 金额: $ 2.57万
• 依托单位: UK CENTRE FOR ECOLOGY & HYDROLOGY
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FV001442%2F1
• 关键词: Runoff; Aerial; Artificial; Intelligence; Land

Real time risk mapping of agricultural catchments is time consuming and for the purposes of flood risk mapping (particularly after an event) is made difficult due to flooding or soil conditions. The challenge is to map the risk factors associated with flooding or agricultural diffuse pollution in a non-invasive - less labour intensive way using an airborne system with built-in intelligence . The added benefit is that the land surface is not damaged at a critical time, and that mitigation strategies can be rapidly deployed.

农业集水区的真实的实时风险绘图是耗时的，并且由于洪水或土壤条件而难以进行洪水风险绘图（特别是在事件发生后）。目前的挑战是，使用具有内置智能的机载系统，以非侵入性、劳动密集程度较低的方式绘制与洪水或农业扩散污染相关的风险因素。额外的好处是，在关键时刻，陆地表面不会受到损害，而且可以迅速部署减灾战略。